Generation New Era

The Data will be used for the purpose of recruitment to a longitudinal research study: Generation New Era (GNE).

GNE aims to collect rich, longitudinal data on a 30,000-strong cohort of infants born across the UK in the mid-2020s. GNE will be the first nationwide birth cohort in a quarter of a century, providing urgently needed data for science, practice and policy on a new generation of children and families. The study will paint a nationally representative picture of the early environments shaping the developmental, social, and health trajectories of children in a period of unprecedented social, technological, and environmental change.

The primary scientific aim of the study will be to understand how variability, and particularly inequalities, in the central domains of early child development emerge over time and to determine the social and biological factors influencing their trajectories.

NHS England data will be used for the recruitment and sampling elements of GNE, including sampling participants in England and Wales for the study from birth registrations linked to birth notifications and using an opt-out approach to recruitment. The selected sample will be sent an initial notification/opt-out letter, followed by an advance letter and booklet. For those who do not opt out of further contact, fieldworkers will then seek consent for participation in the study.

Data will be used to select ‘families’ which the fieldworkers will contact and attempt to recruit to participate in the study. The study will use the ethnicity fields to boost the England sample. The study will use additional fields for targeted fieldwork approaches to maximise engagement and inclusivity. UCL will use information on individual-level characteristics from the Data to conduct non-response analysis to assess population representivity, weighting and adjustment.

Phase 1A: Data for non-response analysis

As part of phase 1, no data will flow to NHS England.

NHS England will provide the relevant records from the Civil Registration Births and Birth Notifications datasets to UCL (the ‘full population de-identified sampling file’) on a quarterly basis. The data will contain no direct identifying data items but will contain a unique person ID which can be used by NHS England to link the data with other record level data it holds.

Phase 1B: Data for sampling

UCL will provide IPSOS with a limited set of fields from Phase 1A required for sampling. The data will be stored on servers at Ipsos. Access is restricted to employees or agents of IPSOS.

Analysts from IPSOS will process the data for the purpose of selecting a random sample of families selected for recruitment to the study.

The data flows described in phases 1a and 1b will occur under a separate Data Sharing Agreement (DARS-NIC-800961-W7P2T).

Phase 2: Data for Fieldwork and Recruitment

To initiate phase 2, IPSOS will transfer a list of unique person ID's for the selected sample to NHS England on a quarterly basis. NHS England will then trace the selected sample of babies, as well as their mothers and fathers. NHS England will then remove any ‘family’ where any member has applied the National Data Opt-Out or where either the baby or mother is deceased or where the baby is not traced.

NHS England will then provide demographic data from the Births Notifications and Births Registrations dataset for the selected sample to IPSOS on a quarterly basis. The data will contain directly identifying data items including Names, NHS Number, Date of Birth, Address and Postcode which are required to facilitate contact with the parents and also enable IPSOS to screen for deaths and obtain latest address information from NHS England on a monthly basis, ahead of each contact attempt (as described in Phase 3 below).

The data flows described in phase 2 will occur under a separate Data Sharing Agreement (DARS-NIC-782449-Z6G3F).

Phase 3: Data for List Cleaning

IPSOS will return direct identifying data items for the selected sample to NHS England. The data will consist of name, NHS Number, Date of Birth, Date of Death, Postcode and unique person ID (as originally supplied by NHS England) for the families selected for recruitment.

NHS England will match the details of each ‘family’ member with the latest Demographics data to identify any deaths, embarkations or no traces, and will apply National Data Opt-Outs to the output. NHS England will then remove any ‘family’ where any member has applied the National Data Opt-Out or where either the baby or mother is deceased or where the baby is not traced. These Demographics records will be returned on a monthly basis to IPSOS.

Agency fieldworkers at IPSOS will use the name and contact details to send an initial letter to the relevant mothers and fathers giving them information about the study and giving an opportunity for respondents to remove themselves from the sample. Additionally, analysts from IPSOS will process the data for the purpose of real time analyses of response rates.

Prior to mailing out further correspondence to potential recruits, IPSOS will upload the details of the cohort, excluding those who opt-out, to NHS England’s Cohort Management System (CMS) and will download reports containing latest vital status and addresses.

The data flows described in phase 3 will occur under this Data Sharing Agreement (DARS-NIC-792066-B5D2T).

IPSOS will extract a pseudonymised subset of the data containing variables necessary for non-response analysis and securely transfer this to UCL.

The data will be stored in UCL’s Data Safe Haven.

The data will be stored on servers at IPSOS.

UCL uses offsite back-up services provided by VIRTUS Data Centres.

UCL stores data on the Cloud provided by Amazon Web Services.

IPSOS will undertake the sampling and recruitment tasks. IPSOS is an organisation with safeguarding measures in place and fieldworkers will be trained to handle sensitive situations and family circumstances.

IPSOS has partnered with Verian and NatCen to deliver the study fieldwork (at phase 1 and 2), therefore Verian and NatCen are acting as a data processor.

Formara are contracted by the fieldwork agency to print the notification (opt out) and invitation (advance) mailings for the project. Ipsos share the data required for the mailings with Formara. This is limited to the data needed: i.e parent name, address, unique identifier, and details needed for the letter mailmerges.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. UCL stores data on the Cloud provided by Amazon Web Services.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:

- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;

- Access controls granting users the minimum level of access required are in place;

- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;

- Multifactor authentication (MFA) is required for remote access;

- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;

- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within UK. The data will not leave the UK at any time.

The data will remain on the servers at UCL at all times. There will be no requirement and no attempt to reidentify individuals when using this data.

Once the fieldwork has concluded, IPSOS will transfer the details, including direct identifiers, of all people who consented to participate to UCL along with the deidentified data for non-respondents and those who declined to participate or opted out of taking part.

IPSOS will retain the data until instructed by UCL to destroy it or contractually required to destroy it. UCL will undertake verification checks on receipt of the data from IPSOS and will instruct deletion when ready. IPSOS are contractually required to delete the data within a fixed duration from the end of their contract with UCL and are obliged under the terms of this DSA to delete the data by its expiry date.

All personnel accessing the data have been appropriately trained in data protection and confidentiality.

The expected outputs of the processing will be:

• A Research resource deposited with the UK Data Archive December 2028 (Wave 1 of the study), available to bona fide researchers for the purposes of statistical data analysis comprised of information collected from the consented participants. The information provided by NHS England will have facilitated the collection of this information. The deposited data will not include the sampling field data provided by NHS England. Researchers from a range of sectors and disciplines will be able to apply to use the data, enabling policy-relevant research and valuable scientific research. The data may also be deposited with other Trusted Research Environments, such as the UK Longitudinal Linkage Collaboration.

• Lessons learned reports for the funder.

• A set of high-quality, open-access substantive/methodological outputs (including reports, working papers, journal articles and conference presentations) including initial findings from the study.

The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:

• Open-access outputs;

• The CLS website https://cls.ucl.ac.uk/cls-studies/

• A participant facing GNE website with its own branding

The target date for production and dissemination of the above outputs is late 2028/early 2029.

Generation New Era is a major research infrastructure project which will collect rich, longitudinal data on a nationally representative, 30,000-strong cohort of infants born across the UK in the mid-2020s. It will be the first nationwide birth cohort in 25 years, providing urgently needed data for science, practice and policy. It aligns directly with ESRC’s infrastructure priorities: building long-term, accessible data assets; addressing key societal challenges; and supporting interdisciplinary, policy-relevant research.

GNE will answer critical questions about how variability, and particularly inequalities, in the central domains of early child development emerge over time and how social and biological factors influence their trajectories. Taking an innovative approach to design and measurement, its first phase will deliver behavioural, cognitive, and health assessments and contextual data from infants and families across two major data collection waves at 9-10 months and 3 years, with additional data captured between waves via a bespoke smartphone app. Linkage to health, education, and social care administrative records will be embedded from the start, capturing short- and long-term data on parent and child health, education and social care use, from pregnancy onwards.

The data will enable a range of important scientific questions to be addressed, leading to strong public benefits. This includes for example, addressing new questions about the relative influence of different home environments and infant-child interactions on infant development, for different sub-groups of families; the role of non-primary caregivers, especially fathers, whether they are co-resident with the baby or in their own households, in supporting infant development and later outcomes, and the factors influencing infant health, weight and growth in the early years.

New data are needed urgently because of unprecedented social, technological, and environmental changes affecting new generations, such as the pervasiveness of digital technology, the rise of AI, new family forms, changing labour markets, cost-of-living pressures and climate change-related risks. It will provide a vital resource to capture future shocks, including global recessions and pandemics. GNE will be unique in its '4 nations' reach, leveraging country-level boosts to deliver high-quality data for the whole nation.

Not stated in the register.